This page has only limited features, please log in for full access.

Unclaimed
Oliver Ohneiser
German Aerospace Center (DLR), Institute of Flight Guidance, Lilienthalplatz 7, 38108, Braunschweig, Germany

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 07 June 2021 in Journal of Air Transport Management
Reads 0
Downloads 0

Air traffic controllers' (ATCos) workload often is a limiting factor for air traffic capacity. Thus, electronic support systems intend to reduce ATCos' workload. Automatic speech recognition can extract controller command elements from verbal clearances to deliver automatic input for air traffic control systems, thereby avoiding manual input. Assistant Based Speech Recognition (ABSR) with high command recognition rates and low error rates has proven to dramatically reduce ATCos’ workload and increase capacity in approach scenarios. However, ABSR needs accurate hypotheses on expected commands and accurate extractions of command annotations from utterance transcriptions to achieve the required performance. Based on the experience of implementation for approach control, a hypotheses generator and a command extractor have been developed for speech recognition applications regarding tower control communication to face current and future challenges in the aerodrome environment. Three human-in-the-loop multiple remote tower simulation studies were performed with 16 ATCos from Hungary, Lithuania, and Finland at DLR Braunschweig from 2017 to 2019. Roughly 100 h of speech with corresponding radar data were recorded. Around 6000 speech utterances resulting in 16,000 commands have been manually transcribed and annotated. Some parts of the data have been used for training prediction models and command extraction algorithms. Other parts were used for evaluation of command prediction and command extraction. The automatic command extractor achieved a command extraction rate of 96.7%. The hypotheses generator showed operational feasibility with a sufficiently low command prediction error rate of 7.3%.

ACS Style

Oliver Ohneiser; Hartmut Helmke; Shruthi Shetty; Matthias Kleinert; Heiko Ehr; Šarūnas Murauskas; Tomas Pagirys. Prediction and extraction of tower controller commands for speech recognition applications. Journal of Air Transport Management 2021, 95, 102089 .

AMA Style

Oliver Ohneiser, Hartmut Helmke, Shruthi Shetty, Matthias Kleinert, Heiko Ehr, Šarūnas Murauskas, Tomas Pagirys. Prediction and extraction of tower controller commands for speech recognition applications. Journal of Air Transport Management. 2021; 95 ():102089.

Chicago/Turabian Style

Oliver Ohneiser; Hartmut Helmke; Shruthi Shetty; Matthias Kleinert; Heiko Ehr; Šarūnas Murauskas; Tomas Pagirys. 2021. "Prediction and extraction of tower controller commands for speech recognition applications." Journal of Air Transport Management 95, no. : 102089.

Journal article
Published: 20 February 2020 in Aerospace
Reads 0
Downloads 0

Current Air Traffic Controller working positions (CWPs) are reaching their capacity owing to increasing levels of air traffic. The multimodal CWP prototype TriControl combines automatic speech recognition, multitouch gestures, and eye-tracking, aiming for more natural and improved human interaction with air traffic control systems. However, the prototype has not yet undergone systematic evaluation with respect to feasibility. This paper evaluates the operational feasibility, focusing on the system usability of the approach CWP TriControl and its fulfillment of operational requirements. Fourteen controllers took part in a simulation study to evaluate the TriControl concept. The active approach controllers among the group of participants served as the main core target subgroup. The ratings of all controllers in the TriControl assessment were, on average, generally in slight agreement, with just a few showing statistical significance. However, the active approach controllers performed better and rated the system much more positively. The active approach controllers were strongly positive regarding the system usability and acceptance of this early-stage prototype. Particularly, ease of use, user-friendliness, and learnability were perceived very positively. Overall, they were also satisfied with the command input procedure, and would use it for their daily work. Thus, the participating controllers encourage further enhancements to be made to TriControl.

ACS Style

Oliver Ohneiser; Marcus Biella; Axel Schmugler; Matt Wallace. Operational Feasibility Analysis of the Multimodal Controller Working Position “TriControl”. Aerospace 2020, 7, 15 .

AMA Style

Oliver Ohneiser, Marcus Biella, Axel Schmugler, Matt Wallace. Operational Feasibility Analysis of the Multimodal Controller Working Position “TriControl”. Aerospace. 2020; 7 (2):15.

Chicago/Turabian Style

Oliver Ohneiser; Marcus Biella; Axel Schmugler; Matt Wallace. 2020. "Operational Feasibility Analysis of the Multimodal Controller Working Position “TriControl”." Aerospace 7, no. 2: 15.

Conference paper
Published: 01 September 2018 in 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC)
Reads 0
Downloads 0

Nowadays Automatic Speech Recognition (ASR) applications are increasingly successful in the air traffic (ATC) domain. Paramount to achieving this is collecting enough data for speech recognition model training. Thousands of hours of ATC communication are recorded every day. However, the transcription of these data sets is resource intense, i.e. writing down the sequence of spoken words, and more importantly, interpreting the relevant semantics. Many different approaches including CPDLC (Controller Pilot Data Link Communications) currently exist in the ATC community for command transcription, a fact that e.g. complicates exchange of transcriptions. The partners of the SESAR funded solution PJ.16-04 are currently developing on a common ontology for transcription of controller-pilot communications, which will harmonize integration of ASR into controller working positions. The resulting ontology is presented in this paper.

ACS Style

Hartmut Helmke; Michael Slotty; Michael Poiger; Damian Ferrer Herrer; Oliver Ohneiser; Nathan Vink; Aneta Cerna; Petri Hartikainen; Billy Josefsson; David Langr; Raquel Garcia Lasheras; Gabriela Marin; Odd Georg Mevatne; Sylvain Moos; Mats N. Nilsson; Mario Boyero Perez. Ontology for Transcription of ATC Speech Commands of SESAR 2020 Solution PJ.16-04. 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC) 2018, 1 -10.

AMA Style

Hartmut Helmke, Michael Slotty, Michael Poiger, Damian Ferrer Herrer, Oliver Ohneiser, Nathan Vink, Aneta Cerna, Petri Hartikainen, Billy Josefsson, David Langr, Raquel Garcia Lasheras, Gabriela Marin, Odd Georg Mevatne, Sylvain Moos, Mats N. Nilsson, Mario Boyero Perez. Ontology for Transcription of ATC Speech Commands of SESAR 2020 Solution PJ.16-04. 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC). 2018; ():1-10.

Chicago/Turabian Style

Hartmut Helmke; Michael Slotty; Michael Poiger; Damian Ferrer Herrer; Oliver Ohneiser; Nathan Vink; Aneta Cerna; Petri Hartikainen; Billy Josefsson; David Langr; Raquel Garcia Lasheras; Gabriela Marin; Odd Georg Mevatne; Sylvain Moos; Mats N. Nilsson; Mario Boyero Perez. 2018. "Ontology for Transcription of ATC Speech Commands of SESAR 2020 Solution PJ.16-04." 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC) , no. : 1-10.

Journal article
Published: 08 May 2018 in Aerospace
Reads 0
Downloads 0

TriControl is a controller working position (CWP) prototype developed by German Aerospace Center (DLR) to enable more natural, efficient, and faster command inputs. The prototype integrates three input modalities: speech recognition, eye tracking, and multi-touch sensing. Air traffic controllers may use all three modalities simultaneously to build commands that will be forwarded to the pilot and to the air traffic management (ATM) system. This paper evaluates possible speed improvements of TriControl compared to conventional systems involving voice transmission and manual data entry. 26 air traffic controllers participated in one of two air traffic control simulation sub-studies, one with each input system. Results show potential of a 15% speed gain for multimodal controller command input in contrast to conventional inputs. Thus, the use and combination of modern human machine interface (HMI) technologies at the CWP can increase controller productivity.

ACS Style

Oliver Ohneiser; Malte Jauer; Jonathan R. Rein; Matt Wallace. Faster Command Input Using the Multimodal Controller Working Position “TriControl”. Aerospace 2018, 5, 54 .

AMA Style

Oliver Ohneiser, Malte Jauer, Jonathan R. Rein, Matt Wallace. Faster Command Input Using the Multimodal Controller Working Position “TriControl”. Aerospace. 2018; 5 (2):54.

Chicago/Turabian Style

Oliver Ohneiser; Malte Jauer; Jonathan R. Rein; Matt Wallace. 2018. "Faster Command Input Using the Multimodal Controller Working Position “TriControl”." Aerospace 5, no. 2: 54.

Conference paper
Published: 01 September 2016 in 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC)
Reads 0
Downloads 0

Air traffic controllers normally manage all aircraft information with flight strips. These strips contain static information about each flight such as call sign or weight category. Additionally, all clearances regarding altitude, speed, and direction are noted by the controller. Historically paper flight strips were in operation, but modern controller working positions use electronic flight strips or electronic aircraft labels. However, independent from the type, considerable controller effort is needed to manually maintain strip information consistent with commands given to the aircraft. Automatic Speech Recognition (ASR) is a solution which requires no additional work from the controller to maintain radar label information. The Assistant Based Speech Recognizer developed by DLR and Saarland University enables command error rates below 2%. Validation trials with controllers from Germany and Austria showed that workload reduction by a factor of three for label maintenance is possible.

ACS Style

Hartmut Helmke; Oliver Ohneiser; Thorsten Muhlhausen; Matthias Wies. Reducing controller workload with automatic speech recognition. 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) 2016, 1 -10.

AMA Style

Hartmut Helmke, Oliver Ohneiser, Thorsten Muhlhausen, Matthias Wies. Reducing controller workload with automatic speech recognition. 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC). 2016; ():1-10.

Chicago/Turabian Style

Hartmut Helmke; Oliver Ohneiser; Thorsten Muhlhausen; Matthias Wies. 2016. "Reducing controller workload with automatic speech recognition." 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) , no. : 1-10.

Conference paper
Published: 01 September 2015 in 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC)
Reads 0
Downloads 0

Nowadays Arrival Managers (AMAN) are available to produce efficient inbound traffic sequences and to create guidance advisories for optimized approaches. Information about deviations from the planned sequence is exchanged between controller and pilot via radio communication. The AMAN is only able to derive these deviations from the radar data. Using radar data as single input sensor, however, results in adaptation delays of 30 seconds and more - and even worse, the controllers' intent is still missing. The AcListant® AMAN (Active Listening Assistant) [1] has shown for the Dusseldorf Approach Area how to avoid this sensor delay by analyzing the controller-pilot-communication and using the gained information as an additional sensor. An Assistant Based Speech Recognition system (ABSR) is embedded in an AMAN, which provides a dynamic minimized world model to the speech recognizer. Validation trials were performed from February to March 2015 with seven male and four female air traffic controllers from Dusseldorf, Frankfurt, Munich, Vienna, and Prague. Depending on the accepted rejection rate of the speech recognizer, recognition rates between 90% and 95% were achieved, whereas without ABSR only rates between 58% and 83% were possible. Furthermore ABSR significantly reduces the deviation between the controllers' plan and the plan of the AMAN and, at the same time, significantly reduces the controllers workload.

ACS Style

Hejar Gürlük; Hartmut Helmke; Matthias Wies; Heiko Ehr; Matthias Kleinert; Thorsten Mühlhausen; Kathleen Muth; Oliver Ohneiser. Assistant based speech recognition - another pair of eyes for the Arrival Manager. 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC) 2015, 3B6-1 -3B6-14.

AMA Style

Hejar Gürlük, Hartmut Helmke, Matthias Wies, Heiko Ehr, Matthias Kleinert, Thorsten Mühlhausen, Kathleen Muth, Oliver Ohneiser. Assistant based speech recognition - another pair of eyes for the Arrival Manager. 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC). 2015; ():3B6-1-3B6-14.

Chicago/Turabian Style

Hejar Gürlük; Hartmut Helmke; Matthias Wies; Heiko Ehr; Matthias Kleinert; Thorsten Mühlhausen; Kathleen Muth; Oliver Ohneiser. 2015. "Assistant based speech recognition - another pair of eyes for the Arrival Manager." 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC) , no. : 3B6-1-3B6-14.

Conference paper
Published: 01 September 2015 in 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC)
Reads 0
Downloads 0

(1) Functionality benefits of ABSR based AMAN on trajectory conformance and sequence stability (2) ABSR positively influences ATCo workload (3) ABSR supports ATCo more effectively than without any sensor or updated with mouse (4) perceived workload regarding conventional method of operation and ABSR is nearly on the same level

ACS Style

Hejar Gürlük; Hartmut Helmke; Matthias Wies; Thorsten Mühlhausen; Heiko Ehr; Matthias Kleinert; Oliver Ohneiser; Kathleen Muth. Assistant based speech recognition - another pair of eyes for the arrival manager. 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC) 2015, 1 -29.

AMA Style

Hejar Gürlük, Hartmut Helmke, Matthias Wies, Thorsten Mühlhausen, Heiko Ehr, Matthias Kleinert, Oliver Ohneiser, Kathleen Muth. Assistant based speech recognition - another pair of eyes for the arrival manager. 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC). 2015; ():1-29.

Chicago/Turabian Style

Hejar Gürlük; Hartmut Helmke; Matthias Wies; Thorsten Mühlhausen; Heiko Ehr; Matthias Kleinert; Oliver Ohneiser; Kathleen Muth. 2015. "Assistant based speech recognition - another pair of eyes for the arrival manager." 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC) , no. : 1-29.

Conference paper
Published: 01 December 2014 in 2014 IEEE Spoken Language Technology Workshop (SLT)
Reads 0
Downloads 0

This paper presents an approach for incorporating situational context information into an on-line Automatic Speech Recognition (ASR) component of an Air Traffic Control (ATC) assistance system to improve recognition performance. Context information is treated as prior information to reduce the search space for recognition. It is integrated in the ASR pipeline by continually updating the recognition network. This is achieved by automatically adapting the underlying grammar whenever new situational knowledge becomes available. The context-dependent recognition network is then re-created and substituted for recognition based on these context-dependent grammars. As a result, the recognizer's search space is constantly being limited to that subset of hypotheses that are deemed plausible in the current situation. Since recognition and adaptation tasks can be easily performed by two separate parallel processes, on-line capabilities of the system are maintained, and response times do not increase as a result of context integration. Experiments conducted on about two hours of ATC data show a reduction in command error rate by a factor of three when context is used.

ACS Style

Anna Schmidt; Youssef Oualil; Oliver Ohneiser; Matthias Kleinert; Marc Schulder; Arif Khan; Hartmut Helmke; Dietrich Klakow. Context-based recognition network adaptation for improving on-line ASR in Air Traffic Control. 2014 IEEE Spoken Language Technology Workshop (SLT) 2014, 13 -18.

AMA Style

Anna Schmidt, Youssef Oualil, Oliver Ohneiser, Matthias Kleinert, Marc Schulder, Arif Khan, Hartmut Helmke, Dietrich Klakow. Context-based recognition network adaptation for improving on-line ASR in Air Traffic Control. 2014 IEEE Spoken Language Technology Workshop (SLT). 2014; ():13-18.

Chicago/Turabian Style

Anna Schmidt; Youssef Oualil; Oliver Ohneiser; Matthias Kleinert; Marc Schulder; Arif Khan; Hartmut Helmke; Dietrich Klakow. 2014. "Context-based recognition network adaptation for improving on-line ASR in Air Traffic Control." 2014 IEEE Spoken Language Technology Workshop (SLT) , no. : 13-18.

Conference paper
Published: 01 January 2013 in Transactions on Petri Nets and Other Models of Concurrency XV
Reads 0
Downloads 0

Human machine interfaces (HMI) in the product division of air traffic management (ATM) are in use for long time spans. For an efficient use of HMIs not only user centered but also migration tolerant designs are important. Migration tolerance therefore means considering future requirements for a long lasting controller HMI life cycle. For efficient ATM, the concept of system wide information management (SWIM) will be introduced. This generates a large amount of additional information that will influence controller work. In this paper, we therefore describe a new controller role called Information-and-Conflict-Manager (ICM) who handles the complexity induced by SWIM. The resulting HMI design draft demonstrates how the integration of data could be managed. ICM also supervises training to support controllers successfully passing future flight guidance transitions.

ACS Style

Oliver Ohneiser; Hejar Gürlük. Migration Tolerant Human Computer Interaction for Air Traffic Controllers. Transactions on Petri Nets and Other Models of Concurrency XV 2013, 8017, 143 -152.

AMA Style

Oliver Ohneiser, Hejar Gürlük. Migration Tolerant Human Computer Interaction for Air Traffic Controllers. Transactions on Petri Nets and Other Models of Concurrency XV. 2013; 8017 ():143-152.

Chicago/Turabian Style

Oliver Ohneiser; Hejar Gürlük. 2013. "Migration Tolerant Human Computer Interaction for Air Traffic Controllers." Transactions on Petri Nets and Other Models of Concurrency XV 8017, no. : 143-152.

Conference paper
Published: 01 January 2013 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Reads 0
Downloads 0

Delay Tolerant Networking (DTN) approaches based on the Bundle Protocol are commonly used within mobile IP based networks. Instead of being isolated applications, the Internet is often used to provide additional services or to route through other parts of the DTN network. A major drawback is that current DTN routing and discovery protocols are not generally applicable in the Internet as there is no common protocol to resolve DTN node names to convergence layer addresses outside a local network. We present Nasdi, an approach based on Distributed Hash Tables which can support naming, routing, notifications and service discovery in a heterogeneous DTN linked by the Internet. We present the architecture and initial evaluations of a Nasdi prototype system we built for the IBR-DTN software.

ACS Style

Sebastian Schildt; Wolf-Bastian Pöttner; Oliver Ohneiser; Lars Wolf. NASDI – Naming and Service Discovery for DTNs in Internet Backbones. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2013, 108 -121.

AMA Style

Sebastian Schildt, Wolf-Bastian Pöttner, Oliver Ohneiser, Lars Wolf. NASDI – Naming and Service Discovery for DTNs in Internet Backbones. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2013; ():108-121.

Chicago/Turabian Style

Sebastian Schildt; Wolf-Bastian Pöttner; Oliver Ohneiser; Lars Wolf. 2013. "NASDI – Naming and Service Discovery for DTNs in Internet Backbones." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , no. : 108-121.